{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:VST3IRP7V7M7OV7N5HUPIKZVL5","short_pith_number":"pith:VST3IRP7","canonical_record":{"source":{"id":"2311.00136","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"q-bio.NC","submitted_at":"2023-10-31T20:17:32Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"da31bdf9f1cd7c6e18be01c6c0c7925f103a4732315bdf370556e0250d24c007","abstract_canon_sha256":"7971971593beda761ce5a95c8fea47d8162d00edbcc0bab26ddbe43ce6a0c3c6"},"schema_version":"1.0"},"canonical_sha256":"aca7b445ffafd9f757ede9e8f42b355f528af3346a08de44c2b5866b17e5193d","source":{"kind":"arxiv","id":"2311.00136","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.00136","created_at":"2026-07-05T07:56:55Z"},{"alias_kind":"arxiv_version","alias_value":"2311.00136v4","created_at":"2026-07-05T07:56:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.00136","created_at":"2026-07-05T07:56:55Z"},{"alias_kind":"pith_short_12","alias_value":"VST3IRP7V7M7","created_at":"2026-07-05T07:56:55Z"},{"alias_kind":"pith_short_16","alias_value":"VST3IRP7V7M7OV7N","created_at":"2026-07-05T07:56:55Z"},{"alias_kind":"pith_short_8","alias_value":"VST3IRP7","created_at":"2026-07-05T07:56:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:VST3IRP7V7M7OV7N5HUPIKZVL5","target":"record","payload":{"canonical_record":{"source":{"id":"2311.00136","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"q-bio.NC","submitted_at":"2023-10-31T20:17:32Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"da31bdf9f1cd7c6e18be01c6c0c7925f103a4732315bdf370556e0250d24c007","abstract_canon_sha256":"7971971593beda761ce5a95c8fea47d8162d00edbcc0bab26ddbe43ce6a0c3c6"},"schema_version":"1.0"},"canonical_sha256":"aca7b445ffafd9f757ede9e8f42b355f528af3346a08de44c2b5866b17e5193d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:56:55.956861Z","signature_b64":"L6oJ661Bm58TDMI4vzoazqHcLZhZBashFQJBo8RS6jcfmAXDUmzZ0BegwQkZJkUg8DLHx1DCDhjqSn9R0VLRDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aca7b445ffafd9f757ede9e8f42b355f528af3346a08de44c2b5866b17e5193d","last_reissued_at":"2026-07-05T07:56:55.956358Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:56:55.956358Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.00136","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:56:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1ffZ7LQV9yWxg2HbaVH+9TjNKDWZkWgw6aeNqVehpuu8jysboFdsYVSyDVCW1T0HTs+Z9WzgDy12oRfSkWUgAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T00:59:28.889363Z"},"content_sha256":"b8295597d15846055bad6d4fc707f7b960c6dc7698013dd0be4f850f1885a8d3","schema_version":"1.0","event_id":"sha256:b8295597d15846055bad6d4fc707f7b960c6dc7698013dd0be4f850f1885a8d3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:VST3IRP7V7M7OV7N5HUPIKZVL5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neuroformer: Multimodal and Multitask Generative Pretraining for Brain Data","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG","cs.NE"],"primary_cat":"q-bio.NC","authors_text":"Antonis Antoniades, Joseph Canzano, Spencer LaVere Smith, William Wang, Yiyi Yu","submitted_at":"2023-10-31T20:17:32Z","abstract_excerpt":"State-of-the-art systems neuroscience experiments yield large-scale multimodal data, and these data sets require new tools for analysis. Inspired by the success of large pretrained models in vision and language domains, we reframe the analysis of large-scale, cellular-resolution neuronal spiking data into an autoregressive spatiotemporal generation problem. Neuroformer is a multimodal, multitask generative pretrained transformer (GPT) model that is specifically designed to handle the intricacies of data in systems neuroscience. It scales linearly with feature size, can process an arbitrary num"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.00136","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2311.00136/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:56:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8RlMRbF+xkpYxakm1kjG+EXoXE2LJsrzgSWx0HmQOkFGbgfW6YbxkzDPdp0XR6rJcspkaqnKCoYki0ga1ZoUBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T00:59:28.889868Z"},"content_sha256":"bf4d6f7b605de58ebf8aefc3942b1ed0c880979065154c810dbca0e2c2d53ffc","schema_version":"1.0","event_id":"sha256:bf4d6f7b605de58ebf8aefc3942b1ed0c880979065154c810dbca0e2c2d53ffc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VST3IRP7V7M7OV7N5HUPIKZVL5/bundle.json","state_url":"https://pith.science/pith/VST3IRP7V7M7OV7N5HUPIKZVL5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VST3IRP7V7M7OV7N5HUPIKZVL5/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T00:59:28Z","links":{"resolver":"https://pith.science/pith/VST3IRP7V7M7OV7N5HUPIKZVL5","bundle":"https://pith.science/pith/VST3IRP7V7M7OV7N5HUPIKZVL5/bundle.json","state":"https://pith.science/pith/VST3IRP7V7M7OV7N5HUPIKZVL5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VST3IRP7V7M7OV7N5HUPIKZVL5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:VST3IRP7V7M7OV7N5HUPIKZVL5","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"7971971593beda761ce5a95c8fea47d8162d00edbcc0bab26ddbe43ce6a0c3c6","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"q-bio.NC","submitted_at":"2023-10-31T20:17:32Z","title_canon_sha256":"da31bdf9f1cd7c6e18be01c6c0c7925f103a4732315bdf370556e0250d24c007"},"schema_version":"1.0","source":{"id":"2311.00136","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.00136","created_at":"2026-07-05T07:56:55Z"},{"alias_kind":"arxiv_version","alias_value":"2311.00136v4","created_at":"2026-07-05T07:56:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.00136","created_at":"2026-07-05T07:56:55Z"},{"alias_kind":"pith_short_12","alias_value":"VST3IRP7V7M7","created_at":"2026-07-05T07:56:55Z"},{"alias_kind":"pith_short_16","alias_value":"VST3IRP7V7M7OV7N","created_at":"2026-07-05T07:56:55Z"},{"alias_kind":"pith_short_8","alias_value":"VST3IRP7","created_at":"2026-07-05T07:56:55Z"}],"graph_snapshots":[{"event_id":"sha256:bf4d6f7b605de58ebf8aefc3942b1ed0c880979065154c810dbca0e2c2d53ffc","target":"graph","created_at":"2026-07-05T07:56:55Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2311.00136/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"State-of-the-art systems neuroscience experiments yield large-scale multimodal data, and these data sets require new tools for analysis. Inspired by the success of large pretrained models in vision and language domains, we reframe the analysis of large-scale, cellular-resolution neuronal spiking data into an autoregressive spatiotemporal generation problem. Neuroformer is a multimodal, multitask generative pretrained transformer (GPT) model that is specifically designed to handle the intricacies of data in systems neuroscience. It scales linearly with feature size, can process an arbitrary num","authors_text":"Antonis Antoniades, Joseph Canzano, Spencer LaVere Smith, William Wang, Yiyi Yu","cross_cats":["cs.LG","cs.NE"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"q-bio.NC","submitted_at":"2023-10-31T20:17:32Z","title":"Neuroformer: Multimodal and Multitask Generative Pretraining for Brain Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.00136","kind":"arxiv","version":4},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:b8295597d15846055bad6d4fc707f7b960c6dc7698013dd0be4f850f1885a8d3","target":"record","created_at":"2026-07-05T07:56:55Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"7971971593beda761ce5a95c8fea47d8162d00edbcc0bab26ddbe43ce6a0c3c6","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"q-bio.NC","submitted_at":"2023-10-31T20:17:32Z","title_canon_sha256":"da31bdf9f1cd7c6e18be01c6c0c7925f103a4732315bdf370556e0250d24c007"},"schema_version":"1.0","source":{"id":"2311.00136","kind":"arxiv","version":4}},"canonical_sha256":"aca7b445ffafd9f757ede9e8f42b355f528af3346a08de44c2b5866b17e5193d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aca7b445ffafd9f757ede9e8f42b355f528af3346a08de44c2b5866b17e5193d","first_computed_at":"2026-07-05T07:56:55.956358Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:56:55.956358Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"L6oJ661Bm58TDMI4vzoazqHcLZhZBashFQJBo8RS6jcfmAXDUmzZ0BegwQkZJkUg8DLHx1DCDhjqSn9R0VLRDw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:56:55.956861Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.00136","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b8295597d15846055bad6d4fc707f7b960c6dc7698013dd0be4f850f1885a8d3","sha256:bf4d6f7b605de58ebf8aefc3942b1ed0c880979065154c810dbca0e2c2d53ffc"],"state_sha256":"e4ed9d9fd0c007594ec366f148f6206d606bfa16d00f9f169fd485d45f3e1027"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fSWFxBHeb4kItizdzyWO/mvZ1yfJNZzW9bklJgbOqrQTuKcoQYLCbBcJi6zXCXk/yYJIqLGAqpTBOvCaHGEpDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T00:59:28.893388Z","bundle_sha256":"bb942c4152f944cebfb3546b0d79675d0f57a82c9aab72bc015d8f55f04cd240"}}